7,760 research outputs found
Preimage problems for deterministic finite automata
Given a subset of states of a deterministic finite automaton and a word
, the preimage is the subset of all states mapped to a state in by the
action of . We study three natural problems concerning words giving certain
preimages. The first problem is whether, for a given subset, there exists a
word \emph{extending} the subset (giving a larger preimage). The second problem
is whether there exists a \emph{totally extending} word (giving the whole set
of states as a preimage)---equivalently, whether there exists an
\emph{avoiding} word for the complementary subset. The third problem is whether
there exists a \emph{resizing} word. We also consider variants where the length
of the word is upper bounded, where the size of the given subset is restricted,
and where the automaton is strongly connected, synchronizing, or binary. We
conclude with a summary of the complexities in all combinations of the cases
Reduction of dynamical biochemical reaction networks in computational biology
Biochemical networks are used in computational biology, to model the static
and dynamical details of systems involved in cell signaling, metabolism, and
regulation of gene expression. Parametric and structural uncertainty, as well
as combinatorial explosion are strong obstacles against analyzing the dynamics
of large models of this type. Multi-scaleness is another property of these
networks, that can be used to get past some of these obstacles. Networks with
many well separated time scales, can be reduced to simpler networks, in a way
that depends only on the orders of magnitude and not on the exact values of the
kinetic parameters. The main idea used for such robust simplifications of
networks is the concept of dominance among model elements, allowing
hierarchical organization of these elements according to their effects on the
network dynamics. This concept finds a natural formulation in tropical
geometry. We revisit, in the light of these new ideas, the main approaches to
model reduction of reaction networks, such as quasi-steady state and
quasi-equilibrium approximations, and provide practical recipes for model
reduction of linear and nonlinear networks. We also discuss the application of
model reduction to backward pruning machine learning techniques
A generalization of a theorem of Hurewicz for quasi-Polish spaces
We identify four countable topological spaces , , , and
which serve as canonical examples of topological spaces which fail to be
quasi-Polish. These four spaces respectively correspond to the , ,
, and -separation axioms. is the space of rationals, is
the natural numbers with the cofinite topology, is an infinite chain
without a top element, and is the set of finite sequences of natural
numbers with the lower topology induced by the prefix ordering. Our main result
is a generalization of Hurewicz's theorem showing that a co-analytic subset of
a quasi-Polish space is either quasi-Polish or else contains a countable
-subset homeomorphic to one of these four spaces
Ordered Reference Dependent Choice
This paper studies how violations of structural assumptions like expected
utility and exponential discounting can be connected to rationality violations
that arise from reference-dependent preferences, even if behavior is fully
standard when the reference is fixed. A reference-dependent generalization of
arbitrarily behavioral postulates captures changing preferences across choice
domains. It gives rise to a linear order that endogenously determines reference
alternatives, which in turn determines the preference parameters for a choice
problem. With canonical models as backbones, preference changes are captured
using known technologies like the concavity of utility functions and the levels
of discount factors. The framework allows us to study risk, time, and social
preferences collectively, where seemingly independent anomalies are
interconnected through the lens of reference-dependent choice
Improving the Upper Bound on the Length of the Shortest Reset Word
We improve the best known upper bound on the length of the shortest reset words of synchronizing automata. The new bound is slightly better than 114 n^3 / 685 + O(n^2). The Cerny conjecture states that (n-1)^2 is an upper bound. So far, the best general upper bound was (n^3-n)/6-1 obtained by J.-E. Pin and P. Frankl in 1982. Despite a number of efforts, it remained unchanged for about 35 years.
To obtain the new upper bound we utilize avoiding words.
A word is avoiding for a state q if after reading the word the automaton cannot be in q. We obtain upper bounds on the length of the shortest avoiding words, and using the approach of Trahtman from 2011 combined with the well-known Frankl theorem from 1982, we improve the general upper bound on the length of the shortest reset words.
For all the bounds, there exist polynomial algorithms finding a word of length not exceeding the bound
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